{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# MAGNETIZATION VECTOR FIELD RECONSTRUCTION: Heterostructure\n",
    "\n",
    "## Notebook Documentation\n",
    "\n",
    "<br>\n",
    "<br>\n",
    "<img alt=\"Creative Commons License\" style=\"border-width:0\" src=\"https://i.creativecommons.org/l/by/4.0/88x31.png\" />\n",
    "Magnetization Vector Field Reconstruction Notebook Documentation is licensed under the Creative Commons Attribution 4.0 International License (2018).\n",
    "To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.\n",
    "\n",
    "Documentation Authors:\n",
    "- Marc Rosanes\n",
    "- Doga Gursoy\n",
    "- Aurelio Hierro\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "# Testing the 3D vector field reconstruction algorithm \n",
    "## From projections taken at two tilt angles for two different dichroisms, towards the reconstructed vector fill object\n",
    "\n",
    "\n",
    "In this notebook we are reconstructing the magnetization vector field thanks to four projection datasets. Two of them for a given tilt axis, using positive and then negative dichroism respectively. The other two for data recorded using an orthogonal tilt axis to the first one, and also using positive and then negative dichroism respectively.\n",
    "\n",
    "In order to reconstruct the magnetization vector, the input projection data must be the logarithm of the transmittance. Thus, each set of the heterostructure projections represents the logarithm of the transmittance. \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Testing the 3D vector field reconstruction algorithm\n",
    "\n",
    "\n",
    "First, let's make the necessary imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "import dxchange\n",
    "import tomopy\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import time"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "...let us load the our input data: the four datasets containing the projections at two different tilt axes and taken at two different dichroisms for each tilt axis. The tilt angles are also loaded.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "xnfile = 'Xt_dNeg_m90-901deg_Tomo.hdf5'\n",
    "xpfile = 'Xt_dPos_m90-901deg_Tomo.hdf5'\n",
    "ynfile = 'Yt_dNeg_m90-901deg_Tomo.hdf5'\n",
    "ypfile = 'Yt_dPos_m90-901deg_Tomo.hdf5'\n",
    "tilts_file = 'FP_m90-90_1deg.txt'\n",
    "\n",
    "xn = dxchange.read_hdf5(xnfile, dataset='/Tomo/data').astype('float32')\n",
    "xp = dxchange.read_hdf5(xpfile, dataset='/Tomo/data').astype('float32')\n",
    "yn = dxchange.read_hdf5(ynfile, dataset='/Tomo/data').astype('float32')\n",
    "yp = dxchange.read_hdf5(ypfile, dataset='/Tomo/data').astype('float32')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "We take the differenced of the logarithms of the transmittance, for projections with a same tilt axis and different dichroism. This is a preprocessing needed if we want to be able to extract the magnetization vector field. \n",
    "\n",
    "The Y projections need to be transposed; tomopy requires as input all the projections given with the axes in the same direction.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(181, 64, 64)\n",
      "(181, 64, 64)\n"
     ]
    }
   ],
   "source": [
    "prj1 = xp-xn\n",
    "prj2 = yp-yn\n",
    "\n",
    "for m in range(prj2.shape[0]):\n",
    "\tprj2[m] = np.transpose(prj2[m]).copy()\n",
    "    \n",
    "prj1 = tomopy.downsample(prj1, level=2, axis=2).copy()\n",
    "prj1 = tomopy.downsample(prj1, level=2, axis=1).copy()\n",
    "prj2 = tomopy.downsample(prj2, level=2, axis=2).copy()\n",
    "prj2 = tomopy.downsample(prj2, level=2, axis=1).copy()\n",
    "\n",
    "print(np.shape(prj1))\n",
    "print(np.shape(prj2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Check the inputs, to see that the given input datasets are correctly loaded."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fe4aaf0ff90>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe4a8112590>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(10, 6))\n",
    "ax1 = fig.add_subplot(1, 2, 1)\n",
    "ax1.imshow(prj1[50,:,:])\n",
    "ax2 = fig.add_subplot(1, 2, 2)\n",
    "ax2.imshow(prj2[50,:,:])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "...we load the tilt angles, we add to them an offset of 90 degrees and we convert to radians:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "ang = np.loadtxt(tilts_file)\n",
    "ang = np.pi/180. * ang\n",
    "ang = -np.array(np.pi/2.+ang, dtype='float32')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Reconstruction\n",
    "\n",
    "Reconstruct the vector magnetization field components (actually it is the quantity $2L^{-1}\\delta\\vec{m}$, the one which is reconstructed), taking as input the projections.  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "300.147086143\n",
      "(64, 64, 64)\n",
      "(64, 64, 64)\n",
      "(64, 64, 64)\n"
     ]
    }
   ],
   "source": [
    "t = time.time()\n",
    "rec1, rec2, rec3 = tomopy.vector2(prj1, prj2, ang, ang, axis1=1, axis2=2, num_iter=100)\n",
    "dxchange.write_tiff(rec1)\n",
    "dxchange.write_tiff(rec2)\n",
    "dxchange.write_tiff(rec3)\n",
    "print (time.time()-t)\n",
    "print(np.shape(rec1))\n",
    "print(np.shape(rec2))\n",
    "print(np.shape(rec3))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "# Visualization of the test results\n",
    "\n",
    "In this section, there are presented the results of the magnetization vector field components obtained thanks to the tomopy vector reconstruction. The magnetization vector components are presented for different depths inside the object. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Results visualization: magnetization vector field components\n",
    "\n",
    "Visualization of the three magnetization vector field components for a certain object reconstruction depth."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fe4a6572710>"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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su79HofzUpncULkI5pnQIJID1iQ0FQ8FhxFn4a988Jz73YuxssTgRsahzNl467jC8I2bXRrTPAe2H6ZNmiLDhZGSZqrGrwFk1G49ba18DAFreXNTQGPNhY8yLxpgXq8PDMx5OoVgLOtlxbMNHG+2gQnEKlrbh+YnasGLzWHvoq7X2eQDPA8Dw3U/ZRcWibGaAms4SeHYr/XQcBTu9QqPRSsz8aETZf+CGbMWxiFOaJboKqefoJZdFztwKGv4VyfZRx2lEzX5IoWXwIavcXuo7cvqRLlg0o5X+TD4eMxQZ7UYWvB3vS14bTnC2427C/FrI2Tx+1N2HyVVKekSMRi3ym3Fyt2yCm9Y+bTaGMLLhdz293MG9XbvN9go34xuJLDnXyqNoeVCO/brdnrPZL/ceAQC8dRiooQmlPK9nNKNpJTYyscN+creY2QhT3SYz4hkRYUrMTPIMLpol1XH7XJRop1ubC29N0ipHIZQJoyETFLFfnkM3hw9DB0ZvMaPhGKfikO6LSByYDfW8hJA2vHvzaWusbS1Cly3SRpfGh1+Ow7XqHbsL0b/nrlHx+lthe7pe5Z6z3d5BsOF6RC+EMvMPgNhbzwZINpfelbbv3qc1sQlSl1dMq6iNfGMHdi6l8MK+i1kz3L+Yclp2Cn2dhL2aKSV4nCcXLHNOaSr1hb/xvqkv5qGzRSsm7szYM9te7AY9Rq+k5IGPJ4kls9nETn/4os2WZPHOymy8YYx5AgBoeeuM+1EoLhJqx4pth9qwYitw1sHGJwBwVpDnAHx8Nd1RKDYKtWPFtkNtWLEV6BL6+n/ACZAeNca8DODvA/hZAL9mjPkQgJcA/FC3wxkYa2A78+WngzPdcVjV5ECsM+70aqLoBsKtUB4Tl8q0VhQWSzv1osyWUFbvZug4bkuzfHYF970tqpb7S7ShydCOfj8ifJgpfpu6TIAQBszbD4Kbqt53bhPOEjp+LAhEx9dJEEr3g91dVtQnSMNbW0Ouzh/6ukI7Xh4FXeOSDH5kZOpBt+iTUqvs+FBQEWRMub6PuKd+D8R1SobUJjU7wndJ9yY7ahOPSm9dmgUxcnUk4YaZLJ82d7wEvJUVgsEgAjVpl7zH0GvRpeeS656QwHF4Lwj++necS8CH0OdC2tcoCG0casU2nI2UZlMQUf8+w693X7mlFIh6oSyL8Y+DiLZ64GpNmWPnAigR6gIZdoP0qfJxXx44rgQuhZrsSq8HZPv0jpciUu9iGbArV+w7qUost6uGrn3PCz3DZtUOH492I8JMy1kv6ltO0Mpi19w5pYEFJrLv+AGpT4Kr1U7IPrlKeiZlQyOVwAWgSzTKjy5Y9cEV90WhWBvUjhXbDrVhxTZj47VRfF5+gllRrJgfaQodDCcysSzqNGElJ/8qJizqCSxASHLFO8/0kadwNOOPaqvQOlPElWWjfdMINarMyu1oBhWtS5JrxX1JGIkM2+L7V+Tim+gnf2pS0BqfZ70bRKDz606INL7hruv4etiOBbvMaHDFxVb2IteZbURL3wu67jn2YmTcrJATfwHAjGZusz2apdkmg3a/IIapEknV6lg0WgsWwfp1ZFOcIEm2YXtpYTaCCFNsxwn0/BS5ORv1szrBcLJYsctt95PwjLjOC80z2/kZ+UyEMlISqsED98z1HwTGiUPmw0VkheTbJPGyyXzOkVxcxZTthd+1GRKCGWKbY4H4+snkf7vu3TG96pbVSFxb3xcOaw73jdnqmhJm1ZnXGjNYc6rtMtsT6zhhWKbmBycb7I2JxZDMBudw46ReR+EisNiY+2Yygkt/3IyA2rMXbMOib70TdzIDYmuKeVhZ37lHO6Xj7kkBLocb03XiNBIisZqvwr7md+7b5KlRKBQKhUJxWbFZZiNhNbJNotF2ximctOERtR9lD8Qsi/Nu+TSscijuFv1DGg1KZoPCOw0zDNKXxrOzljS5YUfNsZxnNGa5MnoJhObCb8d+b3mYhBHJ6kJYe9HjiyL8+37K1wxvtaTRsEM382A2AwDGjxCjcY1S4l4RIcmcinwQMxqRnxgd0MGHvw1gzcaApuBDkRe7pivRp3WlTGCWPKGFuBB9mrq93LsGADicBuZuOidGpKKwP8F6VJzGmX6r/ZyjGddm02xPlwEtbIvJJO7qkXu7PHGN+odhw+F9mjHed4xGHB5PrCfruTIz1ct0WZaBXZD4L+fbD+9RshtiOmRCLs9I0PvFJ0YEYIaO3iyuXHFtH7vq1x0/4d4nxzfd9rO9zPubX9u5aM2WNr5vO5b6GFaWE9I3UKruWJdB4dAshRD7nPPrj1jr3pHQbIyLuE8+3UDYvsGoZKrc5lIBlMSy7N5y13VfVM4tOZkiM5QitJgTqDGT4f8X9sX/FtZ88fcsLdiyriOU2VAoFAqFQrFW6GBDoVAoFArFWrF5gegieIGSbf6WUnsyb3/yU5SwkAvCDppUWTnj8FAKSRwLF0tKMUbZNjOVYJdB7eP+6FiZ8R636QcVD7tKfJiTzbh2qD27gaJ+82+8rDOCWBYICgrU7pH48MBRdZNHQp+8+4Sq8c6DhwUVuU/q1MIkPZtW3JTrEsHaon1sC9iN0ieX1SAj0K3oxKSrpKRaKgXRnoXYjqvEcvs3yhD3fTh19+t4RplcOzzqtXiwvNCzbj47SEJnczVKMCf3ZKbCKmdfjMRxC0Jt2zKK8n4AWSHULXsh8hI9FoGS+6T/MHRq8MBtwKHwRmQW9u4THx7fFD1uOJnt6pC+4tLvRXOdF4aSG6UKke6YswCRqj2Xe0GNyZ/rx8jd9+6w7t6zbqcnj7trXO8K/xcdx3Dm6HnmBcEuR15WzZeDGZDLYxD2PTsitzCLQEtxI4d0nyf0P0Ied59caz23z8mJcBcd0wViMTzvsycMPalNIm248c9MPldT1256lf9vhWu4Sy4VdgHK8GF2dYWKrizSzaQg8AfDYkg3+LLZG5ZrrlAoFAqFQrEcNstsGCweNbXNZJM2MuEM/5ZLK98Us4QfpqQDM6Qs7Y3DpSgoX78hYVkuhMmHY/F0XIa3cvW9LtVUW4SmcTht0i6TFMzXYPHsRZVZx/2UYtlYdFofBIqCqwZOr7p9Tq6E7ea7NJvx1VvFLps61GZ/+YB5HXC8Ltpw8T7XDhY5n7EPzF5MxYWpk51V4jt/HlA2t2vFsV/3RP8uAGBMs0m5nzmFt06qJhPHYbFeIMrfxQzOsqDU1xqRM7D4oYsqvDJr4auphnVp/ZIs69HCmqSQ24d6HW7ZOxIi0IdUt4MYjd5x2JBD37NVlNOK0G3JkpbFRdqwQfNd3KYD5lvC5+oTWoUmFbHHHGpZXJFxpsSAPhKLQQHg5CbVP7npGNv93VAttl9yCgC37/E0sKrzWSxq5G5X8+YNKYhZaC2GLSkqtkH+TYirmf0tiCEwQmjpq64ya8Bs5FC8h4v4XRt1gRP/UX/lv485JQw7KRydNLwb+tQ7di/ggU+al0km1ni+OhpgW7MlWT1lNhQKhUKhUKwVl0ezkUHqt8+GT8YZbSPNRjqUkh5XnpXzTstJGDWXD9wIvGD2IupUnDYWZRI2CoREXx1Skpu24bbYpyniWxUn/EpO1G8nZmLEdljWY8hKtFxBkXx/sxuB2WBGY7br1kk/bfAD0jKKx+Vly5SpSy6ZbDzWJXeUy+6xa9mnKW+mJK+SK9CPPjsbmrE+QzhKB7wvusaS2ZgRY8fLyUz4lhOhgc1dY/9AxT5mOpDbT9VcxwyDSRgO+bl1XSONNJpgN71w73MF0j7lQxvdy+kyyN8+DRt6jcacqmrORaf4+eXfKJFS9OxtSdXXFEuFMKYsU+ac/WNO7x6pG7ADZ3tzSvVdjQSDRnqKft9d251BKMnLzMYJMRqzWdhnxUw0s3FsL7OmoI/TIlRCp9C7734siUip+4K94NBTzsk4EYzhmJJk7fFOwzpOo8DHqynteb0j+sT6DepLIZiR/sCd7/6O61RZhHXHdA0eHtH7eC+8JTjsmK+5mQomJSkRkLt3rVjhq1aZDYVCoVAoFGuFDjYUCoVCoVCsFRfiRulaD2VRWJmVGRY5hCiXBNFncqP9icNymCYLL8fzQNH1jpwosl9yKKLoE2cVTDJ6Ri4PdllQqJwRwjJPweZCXlNIoQ+5P3x2U3kySU0UX9tEHoK2t6NmdcV6SNVxKdvc5Hqg6Gbkbqq4BoEUgXapJNhyr/2azH02CXUbFQq+DF6UjKukDbs9p0h+vGze97rlhCo60Mw6uxvb4AIYUy2Vvlmcjbam61+L+8BulLGh+0z0dBzYGddWiZGosiUS94fsWjGj54l+k24Q490vtM67XJoui0Bvh+37R5SZ9a7bUf9uqIpZHLo4WDMmVXikvItdI1FND17H2X4zoa+hzsp2xWMbu0B7nQtn5mUiFo6yFCRVSeXL1rtW2O2acbf6Ujxi5Zhcfw8P3cu6fiv4cPtHFO7phf5kW8Im0oycUszL7jYOi45rhXBoNrk65uFE+f3HtYrkbefMtFwJttpxy9m+EHxzRk9ODTAKDxFXyMZu043S488+rDYcN5RBpn4K931BVWbTzKWRcJtvHf/Q9n49x7tXmQ2FQqFQKBRrxanMhjHmaQD/G4B3wM1lnrfW/oIx5gaAXwXwDIAvA/hha+3d1p11CBvMFlhNP8iEMzzUYpGa1Acl1ezkyNaH+dFCliqZXO9F7UUhWRQns6gr2WhNrkPCP8iQOa7W5zNaLR7vWVHZz7Mj2SRgLFZNeiOqU1oKebVDN4SfC4HRnEbpcxIaTfdFWCaHtXIkZE+qc2ndEpO6zkmQUtGi3K5e4oBYsQ2fESzenKSZzABUNCMpM2JhXseyuZkUgSa2w1VjAeBq6Wbz1wZueTwPVsz1UuZJ3RR5Wf3lbjF0ZhijxETJ7ep6p1JBKM+Uc+xHSWxC7yQYxeA+MRoP3KywOArMhmc0/LMnEhqlFV2jTpHQO6kdcRFYy3u4LaxYrkvvTbIEBBPF17HK7Dwn+uV8aRSy+vA4sBezCf17etP9tvdasPfBPXpmPLNBAuFjkfRuwqyFs8K5EKYOfDi0s4lqKN+VTQEzg2tocbIsK965/UNiwojJYeGmTBfALAcL7mdXwnEnN9zne/RcHeyHzHTM+PgEZzJzQVKhOWIDPbPBzxO1FWHu/jz5X0yboeeCADqiC7MxB/B3rLXfAODbAfxtY8w3AvgIgBestc8CeIG+KxSXEWrDim2H2rBiq3Eqs2GtfQ3Aa/T5oTHmMwCeBPADAL6Lmn0UwO8C+OmzdsTrKuSPafgk/RCFvnrWojmX8qO/jJ7DV8FjQkSMesPMvhcfHkCPwkPLJBFW5AfuJeGlgo3gSrI1hyQJ9sGnDfedFFMAnhH7qrMydHXBEFPOlInZYJ/hfDcMjacHzGzQDECkHbcJWxKNqLukuU1CX7PMlfc5Lt488iEvOcVcuw13mMazZmLaps/IrGMLYGnATCYDSy6m1G5cLV3yr8cHDwDEKdA5fJb9wPeN0yiNxe5mhnzLnCRJ0B5+JsWMRsQUJLPCSPDUOL0G0oRfRSBr/Ey1R2GugwfhfPv3idF4QPqME+G8n7mdeKZQsoP8XJ1VCLTM7O4cso5NvYfzB+dlrGWINDvp5ZP3vWC9V1P3xe3YbjybAaA+dC/pnTuu0d6r4YDD+1QhecIzd/p+FAyG081XlPRuei2we8xC9MhucDUwKjXZNe/bCjaXmYLeCSUck6/Yh7QvZhbo3TnYDced71EYMLHJ04NwoY4m7vNRz/XlQdg1+n06XhLqCwT9oMloNoLuhL4nIeauPS1zadIvKvTVGPMMgPcD+CSAx+kB4Afh5oJtPmyMedEY82J1eHi+3ioU58S5bfjoaFNdVSiyOK8Nz0/UhhWbR+fBhjFmH8C/BPCT1toHp7VnWGuft9Z+wFr7gXJ//yx9VChWgpXYsCgwpVBsGquw4d6O2rBi8+gU+mqM6cMZ+K9Ya/8V/fyGMeYJa+1rxpgnANzqfNSuApQFm2VdLdxGhsXmMltyuzKm9yW1x6LI+Q7ThqIKasnuAKLaOFuoCIvz1SKZtpVCzYmgd4FsvQXfPlf/JFOLBQUJUtPaKD0RcuuFoW4du04AYLpH14DOO8rwx+4tZpszbpRsCGzA5rL7AAAgAElEQVRDWBhf7yyyatvFzZfBym14SfgQ1My6dMQv2zAjy1lGc3VTKtrDQCja9igG8PH+fQDASPgjhvR5VJKokjI13jsJ/rOTMs7aWIv6EEyHW3KxxBVCEzV2lJU0sYEodDLeLP0dAMopiQCPqMaJoMy9cHvWFIGGHWSetZpdnc1VIRiYnq+Mu3KpTJznxEbfw22btarjaSk9wGwTOYE/vYf9ZqK2STF2n/s0pGJRJxCEnb5aL7ulxzKtrImW1TB0uKBUBwW5bThTMhAEnnU/40ahB5JdLLIOic/gSeHpLCYtqRqr257cPnOq0F2F43KaARaKzvZE1l9/EHr2okAI/i3jYuftk0yiUfbeJGq5M5ZsfyqzYdx/t18C8Blr7T8Sqz4B4Dn6/ByAjy93aIViM1AbVmw71IYV244uzMZ3AvhxAP/RGPMp+u2/B/CzAH7NGPMhAC8B+KHOR10yIdJSyIXvdTmWWOdz6VPIFOnn3D6JReDRJCf+KieikiSNXs3Uq5/CDmj0yeF0nKTLHZDVO5kRKovaMtsZZjA4RI9YDAyFMGnffZ7tU82M3XDCnHyGCRyZ4CY0olPJCUR5otrl+mbuvc8DlGu/GqzehpcEizF3mRFrOcFKXCTWZbJ4dCREoGO64CPrbs6eCTOoXWI2bpSH1Dbc1Cf6uwCAm4PrAICvDG4AAF7uXfNt7k2oQueMGA6R9G5Kn2dTErsVgkEjFsBWnCQrnJdlQWmOaeRVPnzPLZnNAELirt5DqnXyQIS3siB0mohBgfBc5aZuPDPNhCTzOptuL4TXqxTQnYLV2bDBmZ6vRniyuGSNSqMZYTC/M2OBaLKdCKMupvSOpcRbvaNgTMxocNVey/WdhqJ+CglDxzfcu+/kkdApFmYOKBjg8AlRtZttb8I1o0T/qLs9Mj1pnwOq/cLiURarFqJWia8yTOAQWrcvYlv4MZZVmP0OmqGvHNpbD2j7WbgxPqGaXyJabhJdolH+Axab5gdX2x2FYvVQG1ZsO9SGFduOzacrT5N68Wg5N0NIEzst2t8qupXRG/CIVvr6QvgWjRRp2TsOo9f+nCt08rRUOsg4UVCir4CYjbVpNtjvLBmRAacgp2Rkuy50qtoTCXKu0Ax1z+17LpkNauYTd+VkJMisS9zz8iamty5ELy+mtS4yadK60aNp4IhCSosWD2YtHN7MctS07MsQVk5lTrRTX0w1+zRTr82E9hOu9TUKi92jKRRrOHpFsNPXe1cAAHfHjgU5nMnUdu5zTXqHSug5bPIhSovMxF0mXTknZ0rDW2WSpt4hMRoUYhiFtzKjQUtkmA3b5pTmZ022od/atutU9XWDuo51gvVwWTkOz5xZJyF1alRRlRnTiDnlfTKFJzQbnI6e04D3jsI9bTAEu26nkilgzcPJo+634yeELdLm/SP3PB49JZ6dw4SylfoTShdejvm9H/bJqQN6Y7fPwUNa3hPaokRjIlmIwBhlNE1+Bxlmg8tylMk9ACIWDljwr9T/2OENfI6XtKYrVygUCoVCsVZcSCG2Vs1Gh5HTKvykjeJscpTOvkXqTG40WA2Y4aBRu1AsFxNSGtPMyIi0yj4BFzMU0lfMs6uMmjhsR/sehOmBZWZjx804qwMnMpkdhDZTSpk7o6i3KpAeqOSkFXkfpe9lNJuJf8uxQ4301R31Oo1rnmHDLgrGLh+FwNEozFRUSdmzxdtxe2Y4xDpacgrzKtOpgi64TOo1ouTn10qXb2FG06SZ8HfPabo0J/ZiLpy8XCDLQ94Pr3YnbZI4zbQQmyykVhKTwSnIvZ9eMIasi/KRXxnmLyS9k9eijLfLwObYRI404++54301gZN62ThRFBBSyDcKsmX3Iz4Tk1GTLRQnwc76h+54wwcceSKiOog9rvbcy2t6zb3rZNpxTs548ihFedwUtsTsBacWPxDMNK2rRnROIrEcT89n+83out4x9a3i6Bc6N8G2FKT14KiZUthp/9idQzEhe52F7Tide0ikF7oUGBF+WbcwcTnGcUPvU2U2FAqFQqFQrBU62FAoFAqFQrFWXIBA1MS8zRIUTitznVvZlnwmpfkzoa+cQCsqpcA5gLjfmYRWvROiw1goKqvwkbDTDJjPyiRgySXu4u365DIZBd+H3XNuEx/emohBAWBG4a3e/SNcJzZlxaUI1CbLKIETLduSei36fh5soZK0SLjKWtDMRUs4bJ9rlJB/osr4LNhFUotjzHKhnISS2pcFVZVseQtwtdqpiFc8msZ+NysEokz9lpOmgK7Hh/MukrCPAYW19g8pvJXFoDJxF1VyZWGoHQs/DAtCWQwqBaIs9Kxa3CC562Viqj3s72zvr3jfZ9xuzcjWLupyjl7o3wwP5qRevJT7Yzrf0oulmITtqHAxyjGXhhUCdE7URcJQTlLI6QqA4DKeXSV3+G6wiZpCuud828vFJ1kLlzO7LKpBLJYFgILPpYzf7cVUpCng2ip0YCNsksXR3j3V0bZY111M6X0gQm0tBSLw/yAv0pYexdT07YLP54QyGwqFQqFQKNaKjTMbxgI2m9VnNfvPhrC2MBshnEuMxJNqsdFALwn78iFfktkgYVJBo+eemAn1dihDmMl0ipmMQTOrlqHt7I4bZtcirHV+4GaaXMl1RhUF5zJklyajPvxMJudirWpyTYAQhmWS83Y/8rI5yl+Y0tg02ywzc9pWsMBykptBs+COvsYMR8xoyK3bKsj6fXH0tWjKIbIcDsvJwKoyFEqcklEcDpzd3ZuGVOZ3it1c991xKRERz1ClCJQZjT4dZnAYzoYruHIKcp9+fCyqeKZhrfJaMqOREY+2hrzSPmxGVGcyIeCuczK0cPGutxG5KsshjJmWs4z4d04zZ6YKZOVRtm8/uxYXbR6zHYXMEsCfuS8ipJNTg/M7j8NOpdh9duB+m1119rJ3NSSBO+K035wksS/CzZm14O87UsRP2+2RDQ5Dhw+vupdr/35JSxaKBkOq++69Pco8mJycy79HJWvSo1B27tMobMfnzkLUYiqS7PlEany+zX03KIc2hvocUGZDoVAoFArFWnExoa/nhM1MLHIzaZvMvKN98OyEI5jkTL8XrYrQSHhlGh8w3ePibM3LWx65GaLhULupiKviVOaky4gS4+y57eZXm2GtnIKc9RhelyEIkraRrWd3TGYdEuYnR0rlWIwFdEXu3mVTmbdhC2eTPvSVZnlljtkiVC0XQs4O9tgnnNF8pPuQGpEZrRtTwagRTSFlKvSS2I+xdVPFw1Fg0g7n7vPxlPzlE1nEKvYNFyFa0Ws2WJ/BbAYA9B66hj7pET8XMtyUz4GfC6l38qHkGYai8UsT2bBYfxyT/x35BHjbgEWh220ssAeznLLSArGo1cj9KO27oqRe/v0kZuV2l8KZiVmYVeGlNd937ed7nMY72CAnCuOQ/sk1ahsIOExJq2GIhRj0gr0dsSlRSvRqHG4kJ+ziV1g9kIwK7ZOSe129GoRHU0oidjQiDd1Bj7YXTIPh4oXuuWKdBhAYCs+eCx1Jr+euU01lD6qdQOHMqJAmszxGpivvx8US+f7WPXEPUspBNRsKhUKhUCi2ETrYUCgUCoVCsVZciBulVRAoKbuknc9CaTJNcmLQ1D0g95UMs6Jc822hgLwuCfuMQqCIATY107Bhh+XY8XwlZR4tHoiTTAWiIvSV3SeTG45K5KqFQKjg6oWevBRCNnap+Pon4hxTgagcgnoPB1N62di4ZJl+Pg+2XBjKCLVR3MXtCxcA10lpc62kbd0+FnP4E+uMkN02tSjiwaGyBcnN+j4UNrj0Kjifxzt69wAAh8NQ+viQ0s+ezJ1RHY8DpTs1TA+778P74QbuvOmo4OFd5zLp3Tvx68yR+2xPSMTHIlAh3LQsCM2IOVtFoCmEG4TDzLMZRDtgg1VfVwpjET1bbRl7vXCczK0mV0Il3AuzHbJrciXYXrjGc640zXT/ngj35HBUupB1KV5MPhutlU3cKs78OWAXAvVjPzSqWehJ1bfv3dn36/q3nO3uvBGLKwHg6heoaiu5OA6fDM/Z5Dq5b6665d3qIHSKLkfxwJ0Di6RNpgYQVzAux1IR67bjDKa9++K4fRF/C6AvQoT9Y8vXK8rQSs/6LA6rLURFWZ/ttyX8dxVQZkOhUCgUCsVacSqzYYwZAfj3AIbU/tettX/fGPMeAB8DcAPAHwL4cWvtdPGeCBbtSbZs5jcOxaxbZtWMTAKuhgAGMtQtScSCuM5Jegwe1duEtLCz0ChUVKW2pZjFUkKkPgl3+iL0qaAkRZbEeHYYbg8zGuMbbrQ73RcCrDDpXAgveuWlPF8eQC8KVw2nkhXg+essf1sQdhzlMON74GNg830/L1ZuwytALjlXzlDTZF5SBHpYT6J1YykCpY++CGemD+kcXrbZpenYIxQOOxu8ueBMgMk82OlXHvIMzBkVV28FgP4h1YM4zFRt5QRdvnor3QYh3OSkXDYj5jRewMzG2MJQSCOkSsnZUPRFbMkF1UjZqB3LxFsc+sozZw5XlZNyrmLKIbAykWEVt5Hv8ZqSwHHV196RYO6O4n3KdwnXHZnTu8/XMZFEMYk/7RHdYxHSP6Cw1P1XqGKyqC6894dfcft+4zYAYPc//Tq/7sGzjsk4fIpE+eIdzeLR8oTOhRLa9Y9Cnzjcu39/Sm1l4ZURbef2LcPGWcBq6QRZxAqIa555R4e6KbwuWUrwfW5Zdx50YTYmAL7bWvvNAL4FwPcYY74dwM8B+MfW2mcB3AXwofN3R6FYC9SGFW8HqB0rthanMhvWOUM520+f/iyA7wbwY/T7RwH8AwC/eO4etWg2Wn/2GopMSM+Soa/MXniIIVmdMAM+3W5PjibZD9xMNMMzvhkl/toRiWq4WXXFzQ7nu+H2HN+kEK/rzX2yHiNU9OOTDG28VoPOLdJs9FqGrTyd4BTuuUldJglNmvCrsb/MT23+7zNmuHftN2XDMVkWgZN6HfGMW87AOuya9RwRMUTLKjMD3yPb61NniszMPa0oK/s9on4OjAvt2xOlL5nteGf/LgDgWj9oL+4cOed579gZ6M7tsF3/TbevgvQZmAlnNoPT8jMbKFgIQzoOm6QmdyezmKfxeo6c1oP2YXLMRlp9mdvkqjJvAKu242yCvmxDasJFqeny90KOLB/OzEnZzExUWCUWoqTZeS+YC6aHdL/pPdo7ac7YfeLEvrin/N7kBbEtVrwoLEfR0m9GsM/Du+63K59/6NYdhk7VD+g3Tvgl1vVOnO7DJ0fcC+dpRu4z61dmdE7Th+EJNxWF8c7cO34gdBm+SizvW6QusD1+bxi5iOCZI/muLE20zJXXaH2hbjr01RhTGmM+BeAWgN8C8AUA96y1/LZ4GcCTC7b9sDHmRWPMi9XhUa6JQrF2rMyGj9SGFReHs9qxtOH5idqwYvPoNNiw1lbW2m8B8BSAbwPwDblmC7Z93lr7AWvtB8r9vbP3VKE4B1Zmw3tqw4qLw1ntWNpwb0dtWLF5LBX6aq29Z4z5XQDfDuCaMaZHI+qnALy6ig61ZQdtjQxMQlEBBEFQTiDqH0ei6jIH9k2kG4UFoux6sLE7RW7Pue6lkKoaxSrM48dCSNPwSaraSu8CGVo2ve6W891MOC9nbeS6FD70Fg1wjRQrXEVp6GvszkhEnLlrycusCytpK+uu+BtK5yQbrymmcK023GKfXPV11GLEuaqvbejzvpYU1qbuky5yR1m1dkQulQMqy/lo/6FfN+y7dT0KeR28EWbRxVsujDYn/mQXR0P8mQlT9XbTE+K8ltDXTpcnl0E0HDj+fkECUYlNvIsXIvOuDTWiknsE4d5NXiWAeI9SBtFK1nNK/juZuW189mGl3CfheuD3X++YQkmPwr73X3Eb1v/fZ1zbXtjwS//jX4qO+96f/eOwHbkAq+G7AQDzUdjOZ0+dLrY4/l/A10sGI1if5Znd8MKm+Tr5DKIiLQKLZNldNRHuJr4vSbBE/P+DO7ew2yvBqcyGMeYxY8w1+rwD4L8A8BkAvwPgB6nZcwA+vq5OKhTngdqw4u0AtWPFNqMLs/EEgI8aY0q4wcmvWWt/wxjzaQAfM8b8QwB/BOCXztQDHu1mxJw8000rjmYjMzmBl1TbFfE6CR+yyqGvdvGsPBKPDmi4nIhIZaQdC5nMKDNC5X1STYC960F8VNKs8JFd99sbD0MSmvlxnNSlmohOMatCyWuKMddmac4uOCe+ZDb8deJGkqXxQ2BaN89cfZ/LX/7WFB2m8OHD/to1r9OKCI712vAGMMt5eJZIZJUTkTJy4lMWlO7ScYciM9EBfd4lCu1oEGzzBtnuW8zOXQ1x2Wbm7NkkYa4AYGdcE4W+50KsmX3wgs8zMgwXJPBcAVZmx4tqo3hkxKM+qZdP7hWa+HpMIwrRFEmyQmVW2k6+yrhqah3PwN1nnunTMYZhZTWieivD+J+CDAkNfcuFzpIg9R2Pu8M/eNjYzvdD2On89TfccSbvcoeVZlpw32LbLYXolROFlWNK6jURdUwoERoLPSNmmt+7dIEKWU2ZhLq9Y0pGdhT6W1N13HJKYcS0Kltdl0cDHV8ry76bu0Sj/DGA92d+/yKcz1ChuNRQG1a8HaB2rNhmXJ6qryY3E459+YbZi0xyLz8ilrqB7D65PY0eeZTeNgWXoaFc9Y9G5NynKNyoohAmdrP1wxC1P3CzwptXXQTbd9z8kl/3eP8BAOCpwVsAgE8dvduv+/SDJwAA96duenBbsB7TKc0cqPpmbeJwMgCBrSgTzQkQXTMgmfX4VamQRcBwiJr8LVnmwLs8m/RgK8GWIC9VqtXIhanu0hZFxvOZJv7KHzesC1Vf3fJhzf0IbSrq04ymlWNBWx1RJdjX51cBxHbKbJzhNNLCt1xSAiTDIa9Fi04ix1q0MRrMVnC4okik5/Ugue1pu2zoa+MYi8O2s3i7GDSbRZIOW868Q8Iv1lKIlOQ0e+9R6Kuc6c+ZoeXwVLlPTlPOKbelZoPvKW0+26dn4EDYFKcn4IqyorLr/XGf+uYYir3P3vbr3vM//YHbjspGmHeH4B6778pNcArzyXXJTDBrkbAP8n+DT65ooqUEhxaXIiX5nPvO5yT3mbxHo6RerClM2ZL1SOJasbV8okKhUCgUiu2ADjYUCoVCoVCsFZt1o1gsR98k2sTwe2Yn3DZSufEyJ66jRRKWFe2L6aleoMqYkuv1SYzTO12ktjMMZQoe2XNZFN974GpNvH/3L/w6DiV8miptSgyJW3t1crWx7sHYKa6OCrecsNhqJqnkRHEpBaKNLJ+yhC0LaKlpNhsrt5Ui2/yNNi28cxR9fAE03ybAl6otzHWWqevBbr6hyKjJws6ScpAKvZ4XhHrxp2nOK2aWMh6iahz3mLbnGisP6yD0fGXu4rD/fOzEdeziA4ATEjL3KFT74btCqtuKxIPDO9TmfkhBaah+BVd9NZmqrx65uid8fuzqiGqqxMJSGV7L7pO6Jcso79NkMohmM+r6A3OjljaXDV3cQolbBRAuD75+UmOeuJ+iZ9u7Zsj1IEqF8Gd2w/TvBXspJs7aOb2AJffZ7EAKU92B5uRiKUQGUd73fIe2J/cIEOyjvHIDAHD0dY/6dbNdt3/O5GyFi5zfsSbxlUYua748fL1m8n8Lud973DfxPj1wzwO77ecn8rmiJbksq0lYx9Vsp3txLZkog3SX0Nfc/8klocyGQqFQKBSKteLyCEQZOXGiFyAmI8fMdjI3vh+GZZmNWPBoJX2SDsFEhVRDTAYLPQc9NwouCiECLYn9oN9u7Bz7dU/s3AcAfN2uC6F6R+++X+eTJVFooVw3o4Qxu1QK8Gge4scGRRCLAkA1pxGu6Ledc5wpia1aGJlaCEu5Oq6f1LRV3m0TiGZmeV6km9wLAK31UraZ9RBysqXaM+swQ5j6LSCP4uNwNHMmlLRK2opCnRjTdOcexSm+VQUbe3V2zS2JZWPRsgTPKnkGCADFnAV6w0b7Hok2zdz1yrMPVQi5Db9RG3lOvi4EVYadZ+qu+I6IGO2M6LOBmiqT8iN0+hbbh+SkWuumZMTfIWlU8x3N++LZdBQaOqT7RV9leCtXz54d8L+pYGfMkk2pxhQnQpzth33XQ/q/scf2Eg57QsxINSQB9I3AGO8/9ZdonTv+/fcFeymIpJ5epZ0dCPuk8NSqouReFIbbE+G4XAWZ2Rr5LuMEX7M92o+ou1KO6Dg+uaJkkck+OTmjqLfF+0zDiCXbEhKy0Q9rMnBlNhQKhUKhUKwVF89srGiWmh2VtY3UGiGrprmOZ9diFFjQOmY0dkmPMeqFEe5e3/2233MsxBOjwFA8OXR6jHcPnGbjWhGSenFKaHJDYs8ErceTPVdhk9mPu6K+QUHTCK4sOp272zqZhNtb0WwuuJ1bmI25GINWHH7M33PMBjNPklVK27iFZJ5M2ijHamVDbTO/XXLUp2ZRCjqOXOjrrFNS8SY4vHUsjn9MU8wxxeFxKOvMBnt5QBqN2/MrAIBXJtf9updOnC/7lSM3G5Rh2BzKyJMrWZ14uk/nN2P/fFCZFNMh/Ua+adZXtFR9NTLFeOooL0WlzVRr0SXMVSJJAibDZO1XwXTNE4/ElHJiQJlq22sn+LeZeHB9xWm3rIZhXX/PveP4vToROrPZPWeP0wMvfvDrmHVg++JV1b7gDnednexddVqPgXhH3yudzc733YYnN8O5nNzsRec9fjKwieUhscbX3L6u3zj06+7dc+/kgtKV9x8SsyGq3HJyLR+6K9mhtDKreNfWlN6AdXhDkXq9f+T21Tt0z0NPJPUyxCb2Tzi5F1edDdtzUi/TIalX50rBGXwVPCoKhUKhUCguEjrYUCgUCoVCsVZs1o1isBz10iIubLZthlw13CiSwmdqMDfcSut6CPdAQeLPPrlR9sllcjAIYVk3R45ae2zg8u0/Objr172DwlofKV2bAxnrRWACeCTKxY5KVz2zT+LRJ4d3080wJXr8aDpormOXEAtEM+pCrnw7l8JSvj6JWDdCm7sqV+rxqxADypa5a8qFbTg7aD/TpiY3QU7omcsgyoJSdlTI2irsrqvonoypVOa9Krjm7swdzfza1LlKXh5f8+tun7h1HHLNGWzdTmMBG9PrQAjRm5HwrxTblWSzfc48ydVDe2LfXKOC3ISom1VjfZiqDGFNQmVtJcMV6XOudswCd4uNMjRmm2wvWp5lQ+JwznAZafH5ts245ocIPaaqq30Kb44yiE7dbyxYj+o5cdVWElUO7gW3MvvpDJWx9qGzwqZmV91vR5R982Rf1OKZ8/Ycwiqenb0426YZhXOpp7FKmF3WAGDp/EZ3DPWXxKCi24MH5Op46H40M7Hvgetn79Dtp38YrsWsjLNCyxow5ZSuOV17MxFuHw6Bp3BYX+Io55VdUoy/rO0rs6FQKBQKhWKtuBiB6LKzAS8ujL/n2iAX+sp59+V2RTwTiliPMu6gDBPtUzKvXarQenXo1D83h0Eo9PToDgDgib5jH57sBxaCBaG7XDkzcy596mhfxI+NmJGAY1Ae6z3w62oa1R/TKP/eZIfON5zHMYs46Xsp1vEMt6YQP5NLzsVdyc321kBa+O5lGZHtm06yiJfZi7pF8Jlb11a1lRmNWrSZcVIu3yZcR65z8rB2dsIi0DdmIfyPGY3Xx24dsxkAcO/EURRHJ47ZmAshMlceNjxzzEWdcxXPgZjhUmXQghiOMsM4mIrDBcmWJWNRpnaSYe6Y0ZiJGW6azCsTCtsQmIraKq1JvbYRbcLsOl4K4tXXLQnJqsJKZht82OdYiECn/Dwkx0C4tgWJTcsTKXx0K0d0vGJGdiOqYc8oNyKHzo5vCJZswKxDHBoKhNcZr5sJ0Wr/kKrNEsNwZEI4bv8+iTEfkmCThKGlEMtyZVYz5aR1oUuLqusCIVTVJG1cOw5dTewU8JVkfQgsh74KJscLU3Mhzabx05mhzIZCoVAoFIq1ojOzYYwpAbwI4BVr7fcZY94D4GMAbgD4QwA/bq2dtu1j6XTlCzuT7FP+FrEX9BMnjxIzdo6oq3l2JGbQnLiLB4rMZgDAkBiNa8RovJOSdEkNxdN9x2zcIF3GI0VI6sUaDR7l9QVTkE6SZBXOXWpX0XD/ShE0IrOeO87xwI3u7+zsumOIaSUzGfM6k7aaqtSyO8/kQliXZZUWoC1deb69W8aVaM82zl6JDZ/x8Mw+zVBl1vF1a+oyQsKtxdfWsxeZpFwTX7U1POq3qgMAwKszF8760uQRALEu49aJa3Nv7NiPI5ECeUypkn3FTjGbLLjiJXXKNE83y2zM9njK5RZ8tJzCxVA1zLZKrbaUugyeFc7lIdxvKYOSqyjr99Nct2kp0qpsePEBkqUER6CW8RIQs2ueSQ/CSk6ZXS+WKzWPD5EEbMizchEGTZoQZjv6nOp7IKflxLLRg1EL9mt2QPth8ltI56zM+w9EIai9Y2ZCqO1xeK7694mRplDUwRHrV0QF3ONZ1Ce+XgBQjYg1oczptQgRRp+Tn1ECL3GavrIr27B4V3i2o4Od5mx5lZqkZZiNnwDwGfH95wD8Y2vtswDuAvjQ6rqlUKwFasOKbYfasGIr0YnZMMY8BeC/BPA/A/gp46YU3w3gx6jJRwH8AwC/eOq+bBIB0sZMLNxJy29RNErMaMhaVD6pFY0spcK89CnI3W+jQRj23th1jMZTu84h+MzIJeeSqcVZT8FJuXaLkEyGNRrNGJQAP5sVJ9Onzpc0VeybsM9rFKky67upw/2RGxoPCxnN4o54NKMIAjHNMCY2g+jy+qH/BqZwHZXPZ5lNrtKGz4NcATYuluajSaLr0OH6+yp58jjxvqaCI+Dok/uVY8BuT900781x0GXcn5AugxiNKEEcJ32bxfoMIKjlvZYhp9kg/3gt/MZzX8SK9skZoERUSY+pm6qp52gwEzIahaNWmMWUDEWyXTYFepaFRYsAACAASURBVArp3z/rzO8M2120DafJvWybTYpr5NNh5wp+0b64oOVcFDarKZU4Fz+r9gLl4KONWLMxzbAIA2ZE3FIm1+LniVOnSxtOycfyYXh2+g+5c7TP47Bu5036f3GH3tFH86hvAFBMiF2j/zvVbmAMJ1fofCnler0jthu6fXqTbHsHyqRzdO4VRYUxWxQn59qMBq4rs/HzAP4ewv/BRwDcs9byf7yXATy54r4pFKuE2rBi26E2rNhanDrYMMZ8H4Bb1to/kD9nmmaHR8aYDxtjXjTGvFgdHZ2xmwrF2aE2rNh2rNKG5ydqw4rNo4sb5TsBfL8x5nvhyu5dgRthXzPG9GhU/RSAV3MbW2ufB/A8AAyffvpUviaqnZHy5Tm1oA+LjcNcgab7RNYDKcrFQjAWhPaozdWdIMZ8jBJ2cXgri0HZlQGE8FYOXR2JPrEglEMTy4zaldeNxKo+0eAFcXyybgrXSykpPGo8dHTjVcEb7pRO/PfmxFHlh6JqrE/mVXH9lBXSam0+j0y117AuWUaCqKV7sV4b7uDW4bo1Y0vCNrFRldz3jKYyW5k1XTcV/kkWhj6w7j7fiaq2OmEoh7e+NXHulAeTEMZ3TO6TKSVdquaBLvYVhLkCsEzElPRPukxZoxq8GJLuJeo4DdUrBqINUdfkLpTJi0DVYrlqrJmJqq9cU8XXB5K1f+IKsibnYklxMbVRVmbDu4+TDS/rjkxubvY55OsoDJU/s1c3Eg1zUi3fWOyK3t98jeu+COkk10xBIbblkXsfDkXIbe/YvQfnOxx6G2yYxclzNnn5f4NMh4Wpw7fCcfdfc/vnarOy9s/Om852OPmYD9XN/Kuph+5hmO+Ff8Ezqh1U8atZpFzwon1OrCZM34uxZ003oQ9FZpE0/5uMQoz5oq/XnXLqo2Kt/Rlr7VPW2mcA/AiA37bW/k0AvwPgB6nZcwA+vrZeKhTngNqwYtuhNqzYdpwnqddPA/iYMeYfAvgjAL90rp5kRtnMVqTVQW3bLNc0P/sU3YLNKMs4vFXO5lkQutN3Q9wbo8BacAVXTtjFYtCRiJ0aeREnMxtNoWdBM9yowid1gVNLx9tR1T5/jDBzC9ViadRNM78bvZBobEjD3yGJVd+YHPh1U2I0JrRsz1ErPnuiqSlQXPkgOYpXXNleV2vDLah9avCUsmmyFrOWE6wyTFEN3neYuXElV07YxWwGECq43ho7G2DRsAyL9oRSLiFeyiKKJHgsQDODzGyJhaFsZoFc88JSnqXx7K4ahFfUfIfSXtNssHcUngFOj81shxmLBFBcSZbZjp5kaWg7FpG2pDmPFObcJJMEbMPYmA0zfBrvaHaczKCjpF4cDs2sh9gZC4P5u6iwTTkKPXtQDcL1L3bj+FQWXjLDAQAF2UCPbKh3IliyglkEChAQYbGGEpRxKKpMfT+65Sp5969SpeS90KfRHXfs3sMJdZiYmVGw4bpPTCH1f74XbJHT+NcDurBl5iWapIwHgIJfHNw8w6SkIt2IcTyrCS/5jl9qsGGt/V0Av0ufvwjg25Y7nEJxsVAbVmw71IYV24iLSVcuYJJBWafZsZh5W09fNLcPmg0KixLMBusxQMteGYbbV0ZuZHqViqu9cyekBr9JxdWulS5RF2sn4tTixFrQ977wVuVCHxme5bC83eK2Mpy29EyIO+6MkolV4rgDU0Vt+2J6Maep5oyW94WvkIuysU/byoRf/JEPI9elfkAaPkeanPT8usrdLnwyuTyYfRplwgVnaehqttga4jYI95IZDRkqfVw7auCtKi6oBgRWi3U700y2JU4Cx+HfUu/ktRd8T23TJmr/XEt9Az2PvebsjE+Q980zzThxVJp6Weybin31yF8tZ9aYcmeSJSDCYW38PYfcOr+vLTPKZbrrdXG05KRecnacMjxRSnfWbDD7IfftfuuRTk5aPs/6p9eIeT0WzBsVJuuRLfSOKDXAschnlqRO95oGiGoVxIhZoQdhZqOg0G5OxQ4AxZgYFArLZVuUx+OwVjtshuyy7oQZlemBSN1+hdqMqLSB1GzwkvVR8hp6opFPSqxL73NT2rgczmHmmq5coVAoFArFWqGDDYVCoVAoFGvF5t0oFjFX1kbneK8Ci9QyoZIpHyRpemrOVLB0owxJ/FkSPcxVXAHg8R1ylQxc6Ohjg4d+3VVyn/hw05YTYJZXikBD1U8HWamT23FGySKqm1JH60biuEzSsbB0z2Tyk3I9CqLxhiJ2qkrGnFzVEwDmM6Lo6brWMtNeyiBHu4lDtfLuEOb0MtzcZWell+xfsYSaSjKk7BrxlXll9dZEGCrDW1+auXonXxjfBAB85TgIRO9QqOt47iyHhcFcI0cerxV8/6T7jIVo7P6QdRq8y5NsSbo86QtrVLMVnk0scoMRPhZ+1ihUl+nuCJwltBJXmD8nIbAS/N7JrutyW7fI05K/7rRMxIWRi4vdX4V/6Yp9mmgZubpJEOpF+cPgBuG37jHFp7LrAQD6D0gsTBk8+4fOlocPggi0HJNLjdw4s/3w784kmUdljRIM4/OzUqh51a3kSrLSDVIP3DquQMuhs5wBFQjXjkWv02vhYkxukPtkn+q9DIMN1/xsciVcKRBlNw+7AnOewAX30K3LCPzXAGU2FAqFQqFQrBUbZzZMbZAtdNFS1TK0XfZgcdheX4hAmckY9dzyURHe+r692wCAq+UJLUPV1r3CiUdHXL21ZWqTS8Dk62DQurEYhu6aplAv7CvemQz88pVjqc2QxaCyb3wYrttC5xHtk7Z7a7znf5vRrHc8dkes52J8WsUzFVktlhOFRbNeIB9nteyIetVhtRtEPxM+mav2ykgZDRneyqzHPapx8vo8iEC5kiszGrdF3ZPDKc28iEaoiFXgpG4AUNdcM2i5m2MTtirSe6ez5lyYero/cblCWC2ov4IxJDFfj4R7cqbqdbe+booQjzKjUXH9lOY98L/kKsJuqy2mDHNy4eVt983YPIiNqMV/j5pqb7DQUop3A6HVDH21HPpKdrMj6lCVV9xvd6jNySi89SY3SLw5JTaYKgEzwwEA9Pr2M39OmiVPiiu0SqYgZWlkgjImhOcUpjoLj1UjJJj3U4sQbxZJc1jvfC9cjPIR906+cuD+30jN7eEJhadnmQnEkMLpJNw8G/qa1KxpfeRzjFdHKLOhUCgUCoVirdgss2HRGFH7yXe6hGzTMoTy6zL+VFpy2N6gF0aR+wM3iuT04+/auePXfe3odQBBlyErrHIIKYe8crip9HH3k+7KcNeh6VMbd/xcauocvI6D3eSZRGEhBJb1HWH7ivsN6nfZ1HUM6Dzf2L/if5tUzkTu0vdazn5nyVg1FxbLjnleV2XuZQefdjRDXtzs0uJ47qYyr9IsK9JeUBXWMcV9zmwvs84tj8Q06WHlfNlvzl0o61+cPOLXvXToGI03jx3rcTIJvuz5PBVGONTRdJZmRHS/bBUZU7wU4gtf9bUtZJnNJjIXChsskz7ltvcaALGOpmfGxsmegMACFqwjyKQyz1aLTcGhr4KdqtOHvQ0tTMKFYMkZrH9Flzlmg5e+NoTYPt5BlNSLNGBzz7I157/9gbtHs5CHEDUl3GL7ZJueCQ1FQWwHp0mf7Qtr4mqzFDLbOwknXA3jMH8ZqhuSzrl186vhZHxYKv/Ej5moZOuvK7FD5SjY4sG+o2JGpCeciXdtmgtQPl/878knH5PsHD8rZfLMSBaadVZpH0X7nKksmwxMmQ2FQqFQKBRrhQ42FAqFQqFQrBUXk0E0qz5qwrRVBQ2NaEkLqUsqODuoW+4PQljV4yMXWMXuk68ZveHXPdO/HR0iDQ0FRP0TxMcHmiO4KnMCo6T6aw5t2Uaz7WjBTLQklAfEBdY5xw1lHC2ItH73zlt+1UPKMskU+3QmqhSS+fgEmIKaq+kqBHFdho/LCQXfpuCqr8e2+chxHZNxHbtMgJAJ9EG9AwB4U3DJb82ckPeVsavo+/pRcH/dOXbtx1QPgkOYgcQlIpF7Lvm+SX8Gi/oy2Qy9G6WKvwPiUWUTzFWebHGnNropxaPkJeL6EkZy/NZdCxZSm6NQxdlMub9xCKzbLu4Ei2VNFNYZ9y2nfd8qLNPnjMjQh76Ka8cZPDkUlUWZAFBQ6OrxkXMJcpVhILzLOeyzEO+XYhhnHGWhad1vunkNh+vvi3pSA7f9fJdqlTwMx7UjsgGu0yLC/Q25a7jNYD/8T6mon5GIHkBPZAJNPcacORUI9nUydc+/dKPM6b3L9lqOw7XonVDGal9ltpm9tWGLOYHpkva6bBZSZTYUCoVCoVCsFZtlNgwW5mqP2qTr2kLmGFzDQYhxBjR6vbrjZjJP7d3z696369iLpwZuFv9k765fd6Nw7WecgEsMC6f0G9dCYX2YTO41oCH5lEb3dYa9YDaibhlNFh3Hgtwu1GLh0FcRGkh94ORSA6F64hBKrvfyaC8kMXty5K4ZC7hOZmHWzTVl65aTYIbDi8zm8lrE20Wj7xZh0oUyITkb7oCet5dm+OSAKgDXJDyUzMaUQl3vV252/vo0sBevnrhQ11vHju24L5KxcahyxTOxXMhyCpv5nGEXTSIQjap/MqMxbwpF/TrWWUrWw2e5i78XgmhIt4+6zsmS6IGUiZS44IohkW5vLmZ+VPUVtLQyvHVRvZRcErplcdEq50Wn0KVfJhZQus/pfgQLQQnWBvfdQXdvhRn75Lr7fEIM3nQQhMy+j3z55S3lRFtFshR2ntqpFYJ2S2yDZ2Nl4i4fts8Fexa/h+WrnRkNO43byxDtwBSSsNWEf8GTnjt3ZmkwE+9vYoB2brl9794KD8bgLScsNffCe9tvt+v2WU7du6FglkY+V3yaGZtosBe5d0RHKLOhUCgUCoVirejEbBhjvgyXPbYCMLfWfsAYcwPArwJ4BsCXAfywtfbuon0wGqOnFtbCJsMqwyE6MsSSZ8ADNzwbjoIP7caem6m/68B169ndW37d11B467XCtdkVSa586CgN3WZiTMbMwCip4innPkOaoVY0Y5WajRn91k/aAHkGhMEJnzKD/DOhykxt+HzltXik75KdzXbItzoPMw9OxDMhf2IubI3h/ZjysOzn5ZOKpsGrpS9WacNnAYe6Mksmr/+UsiUxi3EswlvfnDsm4y9OHgUAfPEwhLfePnIZhY7G7p5MJ4ERqXh2xbO5iEXooIVqhKQ3WQivvZDrmH2wcdvsvnIhdklYrCxIm1pXtGsTvxusqMZZ92gnnA1M2Bbn/ioOiYmRdsdhsaw/4uezbKZJ3xRWYccWdL3bQnEzM1j/eHpGS8y8uVIqpf/2+gEA5iElqSJmY08wS7ZwuqPBfXofjpp6mDRJlttZ/BuH3ubSKrBNVqPQX64oy+fQOxGny+QDJYgrRVgs75P7WT0IneqNTaO920h8rJJl3WyXtgGCzoUZjb2vhCSU5pXb1BeXsLHYCQxnceLeEb0JhdrSq72YZZ5ZfkVnmENfnT3neeiIZf5n/RVr7bdYaz9A3z8C4AVr7bMAXqDvCsVlhtqw4u0AtWPF1uE8E+QfAPBR+vxRAH/j/N1RKDYKtWHF2wFqx4pLj64CUQvg3xnHm/+v1trnATxurX0NAKy1rxljbnbZUavg5LRO5MQ8FJ7UGzna7pH9UMfkmStO/Pm1e859wq4TAHhH7z4AYEBKmZHgrJhtY7dCKdQ0TH8zaxfCU0Of+Ld+xhXA1VvZtSIZq7QySi3WzmxcP0NmEA31VlrCaBvnFNr2fUVZ99uVMoQGPtp3oqM+FQ+ohViqRwKqOyeUpVKExbJolMVO7BLL9nDZqoNnE9etzIbPgrTqq3SjzNh9Yp375PY8iEC/PHZuk5eOOSNoqFvD9RJmFC4YZXRlt0kulPSixYk5pJ6dDKXLLhVfPFQmqaR1nNFTbleRV4rdKVYUnWDWni23OAzbhdjLWnYxqWi68IzWhbW8i9NXR+TR5CXT7T6kNLThzJrlxDUyDwLNX91+030gwW0xDm7ag7lzDw7vOQH0fEeEaPNNYQo/qvlBuyw55LV5fuxaK6i2STUQz9wenQP1Sbzy/LlTsVn0xs0HJrhvwj7J44wehfim9UhcX2g5s1HfZH+5hox8TjlseHDfyQTK2/f9uuqe+2xnbp3tifDheRx2XJB7NXKjsJi7aB4351Lx67rUMxPoOtj4Tmvtq2TEv2WM+WzXAxhjPgzgwwDQu3b9lNYKxdqwEhsur6sNKy4UZ7JjacP9A7VhxebRabBhrX2VlreMMf8awLcBeMMY8wSNpJ8AcGvBts8DeB4Ahk8/vXgo1DZDSMWjvbAbzi1/7cApfJjNAID/ZP81AMC7B25kfbMMoUFXfG0SZirCEC6tohol7KLffK0Sk07JQihqmbAYEsx+SDaCj9vndWI7/szHldVDi2Qa6Psmjpf6y+R3Xx2WFlwTBgCuFJSvn2rBlDsipI2O16MpD4dgAsB07kxLJpM6C5ZNHLMIK7Phd7XYcAdwleBaiGkrmvpw9daXJjf8upePXcIuZo8mOfYo16P0mZFhg3SjW2sONdAU71pvdtL4mdGi7/L2+z7ZRr9DjaRYPCpnhT5Er4OQTXbX1+0ocxfDiUZHNMPsi5mmn7nNkgtcNK/bphiOs9qxtOGdx5e0YS+0pPcKz8oFs1FOmLVw7w57FBhmO51yJwAA9b0wKy9pFj6kxF/9nUBR2PQ6i+/WJHbSbyoCfNVWss9KtJnvk0CUmIbyRNQ4YWZjlwSiEyloZaaW+xSO1zum5Fokkq0HReM8uIJsMa2ivuXOSQqZOTEaX19UwviT62SkgLlkBoeaZsSn/j56ZkXsrCEUx5lxqmbDGLNnjDngzwD+GoA/AfAJAM9Rs+cAfPzs3VAo1ge1YcXbAWrHim1GF2bjcQD/mkLCegD+hbX2N40xvw/g14wxHwLwEoAf6nLARnrf9EMu/DHRakSV8vacs+1dV1ykF7MZAPA1Q5eC/BFKx31QBMfckIZ2HNZaiuOmCbciLQR3KWkr2Y8aLY4u8PZn0+Z22arRNwBtQ1Kv4/DhvIHZ4DDYXfo+EEPiPn0e0tC4ENdwSql2Z8RsVPOznW+uIuwZJpErteGzoEim4TJx1+3KaTT+7OQdAIAvHYXwVmaLTlrCi9nXKkPCvZKIP0j2wTMiLdOU9EGVTZMEXFZWfaXjhJTkmbuVq/rqQ2X5XOh71CaeedncDCwDbu9DJyMtFXdmiBQ9numRxsCnNM+8DzaEC7fjCC2+fTMMIfLlgbNhS6ngTV/820l1MdPwbveXNhfvn/7GOppMxVPedzkMz1wxd5+ZaSiPp43tfJtppmprpvKw16vMeEkaoVKw0BT2y21kanE+B69NkZVz6bwssRb2YNevKuF0L8wmyWtf0znXFArOz0COMfTVY2VFixYtz7I4dbBhrf0igG/O/P4WgA+e/dAKxWagNqx4O0DtWLHN0AyiCoVCoVAo1orNV301NqumsrnwR/5M7hPOErqzI6q3HjjR59cfOJfJe4ZBG/VYz2VUY7eADG9ll0Fb1s4cUhcFu0OqTDXVnDB0Gci+lYloVK6bJcfOVYtlyVDfu0ya63xtFRHTxteO3SfSxTKieLeD8oS2C/2YEl/Hgsb5nI4i6ynQPTCpMCr9nOAyRm6ehjmFtz6k8qSvz6/6dX96/CQA4E8evNOtOwxCW64AyRUleSk/+5oMuRoMNvkuf1sGcvMiflZNtI6XsThPHjcn4kTiIskJ0kza8a7n4QWO9FVmF+1z6CRdy37IvjgauHvWpyyRPivmNDwDQdTXDBu87Ogsak1d3NkiGm4xP3DuKPOO4Ao0E3e9vBuqFwSMFQlC65FbRqJQesd5G2rz+tELzWQEvoZcF9VQHHdIIaCc+VRWRfYCaOpLr+nO8G4UYUv89jPU3vaac/mK+9kiaLXeFovGOkYxDXZa3nDh8F48KsD3Y77LGVrZnSKuE7tRvO+1sZssrOlqQA7KbCgUCoVCoVgrNs5s2CJJBsIzLk8ZyDC6mNEY7TpG4x1XQgjr1xy4sNZ3DV3IK4tBATErzwg2Q92TxWhLktUGTsCVk4mGGifNtSkTkmMocm0XCVJleGzlz5dC/LLt3fFGgtmoSKTEyc+k0LGk89ylMOL+bpPd4Wqxr8DN5B8KoaifiVsWW0Xxww4ZIdZWDZHplCYUCvz63IWy/snJU77Jp+65z6/cd9doMhXhrVV8srICcYPRyLEXuTooDZV2xs7T3+Q26QwoZ6YsWo00ypm+JB1uPHK58NjMutZzYtbEU3iCXePZJCeHkjPVgXtKRpT5a3DX7YAIU9o+6VPbZG8bWI9MyLG/bcn1k7Pt2a77fHLTMXez/WDDzB74yryi/sl8yMxS88L5MFFfg0es88xX3JdShinb+PjVUPR3J07qNTgSzAbti5OAxVWN43OR/fbhpXS8ulxsDEEILZ7nJFGYTFQWGEM+RlgXEqqNGv3l+8n3h48RPUvcby/SFpu3PXNLYpte2wqFQqFQKLYQm2U2jPuTgyPv9uEhlAzfo3UDSkV+84pjLb7hakg7/t4dV/GOGY2+ac6uGWnKaPmbTN9dGE7KRSNcMd06Pai1HWm6ctnblG2Q7EUby5GiyPjSgsaEmI1MG2ZCRtE1nNI61+++qFJbccVbGm7LsNhyl9Lj0n0d0PTkCzb4cg/nLnzLsp9VDn3T7uU0A5cFLeFhPCs8nLkZ3+fGTwAAPv3gHb4NMxpHx86/Gmkv0kPJGTyzFjn2Iv2tzUG/bEaqTVz+VN+RO/4Zz0nO2oPvOqMjK5OkTGyms0q0STa/ZKbZitwlys1u6fP0EUq8ddUxmfXDkDp//Ijb2fQqMQyi8ikzE57ZEAxDSCWf6R4zUkmotey7T/TGBLmY8fumXqsTfqu4ADA9a5Ox1EfQ4frxMaI+8KMno3jreMm2EZGCyfWNGCROud+LlwBClduS2R7BqNA5F/PFzKE/Jzrv+aOB05+N3YkO72S0c/4gvKPMbx2hzIZCoVAoFIq14gKiUeKvftTHgyqh2eBkRbsjN7t+3xWnz/imvVd8m5Cwy0VElGL4yzPuaWZUVvvoDhqJLzklCYXUmlxHSGFO7EUUOdKdG4lb2sxvyXFXFBmTY4AYZcS20Cibpi67QgHDES3MNO0W7h5O6+Ab/bMTN8yupiEJjeiEQ86HfBmGyG0yB6GdYBLm9r19AMB/GL4PAPCVe9d8m6OHztdqp0Vj+7DzzHHTGX4bCxD18/QpiW3J3mO6HM/P4DLH6phmPNOplj6d2iTYkmzDs8iMDsEX0mI9R0kF7wYhodL0gCMXKFlTTjdzWdmOnG1wOmvBEPSO3Tn9N9//7wAAP3n9ywCA95z816HNmxRNkmEY0pl+3RPvaKZzmWGKWISY2ZAMg89qn6awz50TFx2TjFafI1VMo7+eteDCf7lnzjMbghFnZiFlNspmp9qYDb4Wue18ZySzMePiaryjzEPA+scnXGLLL33XL/tVP/alvwIA+Oz//vWu+4OMDeegzIZCoVAoFIrLBB1sKBQKhUKhWCs260axAOoFVNe0mZiI2aC7M0dBf3L+bgDA5+8/5tv0S8f79YiXMmLnRXKgom2d4It2e47yZ1dLFG5In3sFVzytG21433PiyOS6XlJEYC54tLRPbZD7ZPFl4fvSHEOmfYmuRcKVHc8Hje38eQruLN1OhsVyEisO+WSBJLsTAKC6734rTpgDFTtrEV2iRUB5EUjdJzlx3eyuc5X8WX0TAFCNxaPHNC+dV+dqrKk74owuiNwDaTpwpFkXSSowzLpaTneHpPs77bfEGxs3SX40mXX+kRHUNdPJnp0mF8t8J9y7Kedm4+3lPbmk7hMDus6ZUFKv0xduBb42v/KlbwMA/N699wAAhi8HSXv/QeyqyIXOssukEKbvXQ2JCBfIuE8ydtPFfZaLGfBJwOpMG+4KuzUywtSwH9nf2I3ir4UU4ycGngvp575F61IbltfJ1zTJuV/ZJUMC3gfunfvzd5/xTT5/97H4uJm6KaHDzUN0hTIbCoVCoVAo1oqNC0QbMxcSrhTjdG4iRoo0fBy/6UZlrxYhnXNjRNsWtqPYPBKRnBdRAegnM47cSD6bGfmSzhjbwOxNZYg1ihLnJDOijgxFp+vQRaS4ZNrhxr7lrtLjde3vonUtLEZbuyiFepfrlM5mAd9hZvM4H10l9MzViKfWi/ubPdxlsGF5jVKGR6xjRmL+f7vqop+tXPj6cGQabXyIpbiO1ierslEbAGL2z40z6/y1Xe6iedYjDU8WsI0Pcgenr4vfT2e4qbl3Xq6dbfnKlVyzglJaR8s+JaZ7/mPfGzZ3xWJRE+kcsSZVsjwHc6fMhkKhUCgUirWiE7NhjLkG4J8C+Ca48czfAvA5AL8K4BkAXwbww9bau+07Wi5skZM3tWVOlvs+Fy7DTONtjKxvtSXVcwiJXs2NWZkNtx6EHapN3VFrkjIyPtOJYbDiE2s8uvQtu4v4e9dnqE1PkzAarUm5lkSje11ZhLR9y3a5mVvDdnPJ53KJ1VaMjdhwC1vlk1xxGm4pRUhSipeCtbScdGra3K71/0FGn3AmLMtapG1yu2z7H7Ts85Rsv/CdEXVAbNbh+vjQYNaoyNBkuldlhllt1V4tia7/+n8BwG9aa78ewDcD+AyAjwB4wVr7LIAX6LtCcVmhNqzYdqgNK7YWpw42jDFXAPznAH4JAKy1U2vtPQA/AOCj1OyjAP7GujqpUJwHasOKbYfasGLb0cWN8l4AtwH8c2PMNwP4AwA/AeBxa+1rAGCtfc0Yc7PTEVNqqAONlRUPLYPL7CKRfXsbC1l9xr+i6QbwyMZEr+Twq7dh0VV/bhlXkUls14en5ej6Zan4ZWjmLnRxps2SEbMNn0XjHkdtTkdUZyb90EJlL91vvncy7I+WFQnvcpTyBrPZrtaGF9iDyVzbhjjQxr/L5q3uhVSEftirUgAABsNJREFUKruzBiF423N5ZrTt45xulC7Zb0Pj5fbdCJ2V9y7NZppzi2aw7PXs8qj0AHwrgF+01r4fwBGWoOqMMR82xrxojHmxOjxarncKxWqgNqzYdqzMhucnasOKzaMLs/EygJettZ+k778OZ+RvGGOeoNH0EwBu5Ta21j4P4HkAGL7raZ7unA3nZTjOik0db53HuSSsSTTrb6neupJZSMDqbTgnuGwoEcOPJYvjeNlVONlhpr40OoSL+1nhGdmmMHttU2N22E/byjZBcSak8MyVKxvhvJmu5BKcrRYrs+Hdx58+/U2TCX/s0r6VjWCbkuLRpmZ0Zehg5h1XrqD9OnGW/xs5EeiacSqzYa19HcBXjDFfRz99EMCnAXwCwHP023MAPr6WHioU54TasGLboTas2HZ0Ter13wH4FWPMAMAXAfxXcAOVXzPGfAjASwB+qPNR28Lwlt1+HbjMGo+z4owhXitDZlbZaba+ur6t1oa7ImEm0mqV7seoadtuOqOTCSc7XSV7kpvhNvbfqvloaZNZ57Ux9CFOELcEu9LGWuSYjZbpWqoVWEEU94XY8MLwxy73Dx1DOTuGebb+tgQa6RSW3cF52fku+15B6GuXpJcrZpEXotNgw1r7KQAfyKz64Gq7o1CsB2rDim2H2rBim6EZRBUKhUKhUKwVG6+N0sAytNI6sKJ9X4paB4SlabFlM1CeB133c5kEWCuAd6OUTZ8J0/S2bqwKt6aNij6niywfrni6b2dpO1uWKgfy06EMzRyye7b0u0MG0bh93n0SheN2oLwv07uhK7JZYVO0tDEtdUziKqjxMhKQd7lfS9hgdt8tu9mIe+GMz7PN2f4q+7AGKLOhUCgUCoVirTB2yUp65zqYMbfh4sPf3NhBV4dHof3eJLr0+93W2sc20RmG2vCFYVv7flq/1YaXx9vVFi4rVmLDGx1sAIAx5kVrbU7kdKmh/d4sLnO/L3Pf2rCt/Qa2t++Xtd+XtV9dsK19/2rvt7pRFAqFQqFQrBU62FAoFAqFQrFWXMRg4/kLOOYqoP3eLC5zvy9z39qwrf0Gtrfvl7Xfl7VfXbCtff+q7vfGNRsKhUKhUCi+uqBuFIVCoVAoFGvFxgYbxpjvMcZ8zhjz58aYzqWRLwLGmKeNMb9jjPmMMeZPjTE/Qb/fMMb8ljHm87S8ftF9TWGMKY0xf2SM+Q36/h5jzCepz79KdRUuHYwx14wxv26M+Sxd9++4jNd7W+x4m20Y2E47VhteLdSGN4912vBGBhvGmBLAPwHw1wF8I4AfNcZ84yaOfUbMAfwda+03APh2AH+b+vsRAC9Ya58F8AJ9v2z4CQCfEd9/DsA/pj7fBfChC+nV6fgFAL9prf16AN8Mdw6X6npvmR1vsw0D22nHasOrhdrw5rE+G7bWrv0PwHcA+Lfi+88A+JlNHHtF/f84gL8K4HMAnqDfngDwuYvuW9LPp8gYvhvAb8Alon0TQC93Hy7LH4ArAL4E0hCJ3y/V9d5mO94WG6Z+bZ0dqw1vpO9qw+vt81pteFNulCcBfEV8f5l+u/QwxjwD4P0APgngcWvtawBAy5sX17Msfh7A3wPARaEfAXDPWjun75f1ur8XwG0A/5xox39qjNnD5bveW2nHW2bDwHbasdrwGqE2vBGs1YY3NdhYttzMpYAxZh/AvwTwk9baBxfdnzYYY74PwC1r7R/InzNNL+N17wH4VgC/aK19P1wq5ctIjW7L9fTYJhsGttqO1YbXBLXhjWGtNrypwcbLAJ4W358C8OqGjn0mGGP6cAb+K9baf0U/v2GMeYLWPwHg1kX1L4PvBPD9xpgvA/gYHH338wCuGWO4uu9lve4vA3jZWvtJ+v7rcEZ/2a73VtnxFtowsL12rDa8BqgNbxRrteFNDTZ+H8CzpMYdAPgRAJ/Y0LGXhjHGAPglAJ+x1v4jseoTAJ6jz8/B+RAvBay1P2Otfcpa+wzc9f1ta+3fBPA7AH6Qml2qPjOsta8D+Iox5uvopw8C+DQu3/XeGjveRhsGtteO1YZXD7XhzWLtNrxB8cn3AvgzAF8A8D9ctBjmlL7+Z3AU1x8D+BT9fS+c3+0FAJ+n5Y2L7uuC/n8XgN+gz+8F8HsA/hzA/wlgeNH9W9DnbwHwIl3z/wvA9ct4vbfFjrfdhukctsqO1YZX3k+14c33d202rBlEFQqFQqFQrBWaQVShUCgUCsVaoYMNhUKhUCgUa4UONhQKhUKhUKwVOthQKBQKhUKxVuhgQ6FQKBQKxVqhgw2FQqFQKBRrhQ42FAqFQqFQrBU62FAoFAqFQrFW/P8EpoiDaheFBQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe4a788b690>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(9, 7))\n",
    "ax1 = fig.add_subplot(1, 3, 1)\n",
    "ax1.imshow(rec1[28,:,:])\n",
    "ax2 = fig.add_subplot(1, 3, 2)\n",
    "ax2.imshow(rec2[28,:,:])\n",
    "ax3 = fig.add_subplot(1, 3, 3)\n",
    "ax3.imshow(rec3[28,:,:])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Results visualization: magnetization vector field components\n",
    "\n",
    "Visualization of the three magnetization vector field components for another second object reconstruction depth.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fe4a63c0810>"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe4a6543410>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(9, 7))\n",
    "ax1 = fig.add_subplot(1, 3, 1)\n",
    "ax1.imshow(rec1[34,:,:])\n",
    "ax2 = fig.add_subplot(1, 3, 2)\n",
    "ax2.imshow(rec2[34,:,:])\n",
    "ax3 = fig.add_subplot(1, 3, 3)\n",
    "ax3.imshow(rec3[34,:,:])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Results visualization: magnetization vector field components\n",
    "\n",
    "Visualization of the three magnetization vector field components for another third object reconstruction depth.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fe4a615a890>"
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe4a63b0d10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(9, 7))\n",
    "ax1 = fig.add_subplot(1, 3, 1)\n",
    "ax1.imshow(rec1[30,:,:])\n",
    "ax2 = fig.add_subplot(1, 3, 2)\n",
    "ax2.imshow(rec2[30,:,:])\n",
    "ax3 = fig.add_subplot(1, 3, 3)\n",
    "ax3.imshow(rec3[30,:,:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "celltoolbar": "Slideshow",
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
